System and method to detect and address overweigh perceived by a subject in a salient situation

A non-transitory computer-readable medium having program code recorded thereon for information overweigh detection and intervention, the program code being executed by a processor and comprising:

• program code to train a statistical model to classify salient information regarding events experienced by individuals or to which the individuals are exposed, in which a likelihood of a reoccurrence of the events may be overweighed by the individuals to provide a trained statistical model;
• program code to collect data from a user about the salient information regarding events experienced by the user or to which the user is exposed, wherein the user device comprises a neural network processor, a natural language processor, and one or more cameras, and wherein the program code to collect the data comprises processing at least one of video and speech of the user via the neural network processor, the natural language processor, and the one or more cameras;
• program code to analyze the salient information using the trained statistical model to classify the salient information and identify an event experienced by the user or to which the user is exposed, in which a likelihood of a reoccurrence of the identified event may be overweighed by the user, wherein the program code to analyze further comprises program code to determine a type of overweigh comprising a statistical overweigh and an emotional overweigh;
• program code to present one or more interventions to the user to prevent the user from overweighing the likelihood of the reoccurrence of the identified event;
• and
• tracking, by an intervention tracking model on the user device, user reactions to the one or more interventions to update the trained statistical model on the server computer.

A system for information overweigh detection and intervention, the system comprising:

• an overweigh information training module to train a statistical model, on a server computer, to classify salient information regarding events experienced by individuals or to which the individuals are exposed, in which a likelihood of a reoccurrence of the events may be overweighed by the individuals to provide a trained statistical model;
• a data collection module to collect data from a user about the salient information regarding events experienced by the user or to which the user is exposed, wherein the user device comprises a neural network processor, a natural language processor, and one or more cameras, and wherein to collect the data comprises processing at least one of video and speech of the user via the neural network processor, the natural language processor, and the one or more cameras;
• an overweighed information detection model to analyze the salient information using the trained statistical model to classify the salient information and identify an event experienced by the user or to which the user is exposed, in which a likelihood of a reoccurrence of the identified event may be overweighed by the user, wherein to analyze further comprises to determine a type of overweigh comprising a statistical overweigh and an emotional overweigh;
• and
• an intervention presentation and tracking model to present one or more interventions to the user to prevent the user from overweighing the likelihood of the reoccurrence of the identified event and to track user reactions to the one or more interventions to update the trained statistical model on the server computer.